Literature DB >> 18007573

Predicting antipsychotic use in children.

Ken Gersing1, Bruce Burchett, John March, Truls Ostbye, K Ranga Rama Krishnan.   

Abstract

UNLABELLED: Psychotropic medications are increasingly being used by children and adolescents. In an earlier report, we noted that boys were receiving atypical antipsychotics more frequently than were girls, (70% of the claims). Since diagnosis was not available in the data, we were unable to ascertain the reasons for this. In the present analysis, we examined a large clinical mental health database to ascertain the reason for antipsychotic use.We evaluated the extent to which race, gender, age and type of diagnosis accounted for atypical antipsychotic use in children.
METHODS: The authors used an anonymous clinical database created at Duke University Medical Center. The database is based on the clinical document of care in the Department of Psychiatry. The data are de-identified per HIPAA guidelines and has an IRB exemption for use in clinical research. Patients analyzed were seen from 1999 to 2005 and were below the age of 18 at the time of clinical care. A total 3,268 patients, with a total of 7,701 visits comprise the analysis sample. Age, gender, race, and diagnosis were extracted as predictors of use of atypical antipsychotics.
RESULTS: Males and older children were also more likely to use an atypical. African Americans were slightly more likely to use an atypical than whites. Patients whose diagnoses were classified as either psychotic or internalizing were also more likely to use an antipsychotic.
CONCLUSION: The underlying reasons for the high level of use of atypicals in boys and in African Americans need to be investigated further.

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Year:  2007        PMID: 18007573

Source DB:  PubMed          Journal:  Psychopharmacol Bull        ISSN: 0048-5764


  3 in total

1.  Substance use disorders and comorbid Axis I and II psychiatric disorders among young psychiatric patients: findings from a large electronic health records database.

Authors:  Li-Tzy Wu; Ken Gersing; Bruce Burchett; George E Woody; Dan G Blazer
Journal:  J Psychiatr Res       Date:  2011-07-13       Impact factor: 4.791

2.  Using electronic health records data to assess comorbidities of substance use and psychiatric diagnoses and treatment settings among adults.

Authors:  Li-Tzy Wu; Kenneth R Gersing; Marvin S Swartz; Bruce Burchett; Ting-Kai Li; Dan G Blazer
Journal:  J Psychiatr Res       Date:  2013-01-19       Impact factor: 4.791

3.  Comorbid substance use disorders with other Axis I and II mental disorders among treatment-seeking Asian Americans, Native Hawaiians/Pacific Islanders, and mixed-race people.

Authors:  Li-Tzy Wu; Dan G Blazer; Kenneth R Gersing; Bruce Burchett; Marvin S Swartz; Paolo Mannelli
Journal:  J Psychiatr Res       Date:  2013-09-09       Impact factor: 4.791

  3 in total

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